With the onset of the 2020 pandemic, customers do not want to step out of their homes and interact with humans in person. Conversational AI enables them to resolve their queries and complete tasks from the comfort of their homes. Be it finding information on a product/service, shopping, seeking support, or sharing documents for KYC, they can do this without compromising on personalisation.

This way it narrows down the answer based on customer data and personalizes the responses. Apart from this process, a Conversational AI continually learns from its users. That is, with every conversation, the application becomes smarter by learning through its own mistakes using Machine Learning . This feature helps brands solve many challenges like the use of advanced languages, change in dialects, use of short forms, slang, or jargon. Chatbots can be spread across all social media platforms, websites, and apps, and help marketing, sales, and customer success team via omnichannel. This is because of the timely response received by the potential customers.

What are the top use cases of conversational AI?

Chatbot – short for chatterbot – can be embedded through any major messaging application. With the development of conversational AI, opportunities for developers to create user-friendly AI assistance applications are also becoming possible. Self-aware AI possesses human-level consciousness similar to what Hollywood envisions AI dystopia science fiction.

This technology leverages Natural Language Processing , Speech-to-Text recognition, and Machine Learning to simulate conversations. Starbucks’ “Deep Brew” initiative uses machine learning algorithms that take into account things like the weather, time of day, store inventory, popularity, and community preferences. This allows Starbucks to customize the ordering process and also helps undecided customers choose a beverage faster by showing them what other guests prefer. EVA generates leads by instantly acting upon positive user intent and presenting a service/product that meets their preferences. The conversational banking chatbot solution has resolved over 14.6 Million queries with an accuracy of over 95.5% to date.

Communicates in multiple languages

Conversational AI systems are built for open-ended questions, and the possibilities are limitless. NLU stands for Natural Language Understanding—the ability of a computer system to interpret natural language commands given by users. AI converts the input into actions on its own with the rules stored in its memory banks (e.g., when you ask Google Assistant about directions from your current location). Conversational AI-powered chats can ask the customer for information, collect and process it, and then send it off to a member of your sales team. By implementing the best conversational AI chatbot, your business can ensure the prospects get 24×7 live support and assistance throughout their buying journey.

what is a key differentiator of conversational ai chatbots need to have scripts written by human agents behind the scenes, and they are told specifically what to do as a response to specific keywords. A conversational AI chatbot progressively learns the responses it needs to give to carry out a successful conversation. One of the biggest benefits of using conversational AI is the quick and accurate responses users get. As soon as customers input their queries, they get a response from the chatbot or voicebot. A well-trained AI replies with accurate information, allowing the customer to resolve their questions with self-service.

User Adoption

Another data suggests that a majority of customers prefer messaging over phone calls. With all this happening around you and the kind of expectations consumers have with businesses, it only makes sense that businesses integrate messengers across verticals. Businesses can leverage the potential of Conversational AI by automating customer-facing touchpoints across social media platforms like Facebook, Twitter, and their websites/apps.

• Businesses that use Conversational AI have seen a rapid increase in their CSAT scores by a minimum of 20%.
• Today’s conversational AI chatbots can be predictive and highly personalized.
• These tools also analyse ongoing conversations to retrieve knowledge for agents during interactions with customers in order to determine the best course forward.
• This includes creating conversational flows, responding to end-users, analysing data, changing settings, etc.
• They can recognize the meaning of human utterances and generate new messages dynamically.
• Use multi-channel conversational AI robots to collect and process customer feedback automatically and provide a superior customer experience.

Similarly, if you need assistance in getting started, you can get in touch with us, and we can help you get acquainted with the tech and assist you with the implementation process. It reduces the wait time to get in touch with a medical professional and allows the professional to get to address the patient’s issue faster. Because of their ability to sound human-like and having the convenience of voice search, AI-enabled devices are becoming valuable helpers to customers.

Industries  that are using  Conversational AI

Nothing could have prepared enterprises for the effects of Covid-19 on every aspect of business. The risk of future pandemics, or other risks such as climate change, could also affect companies similarly in the future. Businesses must strengthen their crisis management strategies and deliver resilience, flexibility and scalability into their operations.

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What is the difference between chatbot and conversational AI?

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• The impact on scale is one thing we need to consider when determining the key factor for acting.
• With more interactions with humans, Conversational AI will continue to move towards perfection.
• Just like when we learn a new language, Conversational AI learns best from real-time interactions — and that means it takes time to improve.
• 5 levels of conversational AI – The 5 levels for both user and developer experience categorise conversational AI based on its complexity.
• Rule-based chatbots follow a set of rules in order to respond to a user’s input.
• This intuitive technology enhances customer experiences by letting intent drive the communication naturally.